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J. R. Beck, Garcia, M. E., Zhong, M., Georgiopoulos, M., and Anagnostopoulos, G. C., “A Backward adjusting strategy for the C4.5 decision tree classifier, and the effect of the C4.5 parameters on the tree’s performance”, in 21st Artificial Intelligence Research Symposium, Coconut Grove, FL, 2008.

G. Bebis, Georgiopoulos, M., and Kasparis, T., “Coupling weight elimination with genetic algorithms to reduce network size and preserve generalization”, Neurocomputing, pp. 167–194, 1997.

G. Bebis, Papadourakis, G. M., and Georgiopoulos, M., “Back-Propagation: Increasing rate of convergence by predictable pattern loading”, vol. 1, pp. 14-30, 1989.

G. Bebis, Papadourakis, G. M., Georgiopoulos, M., and Heileman, G. L., “Increasing classification accuracy using multiple-neural-network schemes”, in Proceedings of the 1992 SPIE Conference (Technical Program on Intelligent Information Systems), Orlando, FL, 1992.

G. Bebis and Georgiopoulos, M., “Optimal feed-forward neural network architectures”, IEEE Potentials, pp. 27-31, 1994.

G. Bebis, Georgiopoulos, M., and da Lobo, V. N., “Learning geometric hashing functions for model-based object recognition”, in Fifth International Conference on Computer Vision, ICCV-1995, Cambridge, MA, 1995.

G. Bebis and Georgiopoulos, M., “Improving generalization by using genetic algorithms to determine the neural network size”, in Southcon 95, 1995.

G. Bebis, Georgiopoulos, M., da Lobo, V. N., and Shah, M., “Learning affine transformations of the plane for model-based object recognition”, in 13th International Conference on Pattern Recognition (ICPR-96), Vienna, Austria, 1996.

G. Bebis, Georgiopoulos, M., and Kasparis, T., “Coupling weight elimination and genetic algorithms”, in International Conference on Neural Networks (ICNN), Washington, DC, 1996.

G. Bebis, Georgiopoulos, M., and Bhatia, S., “Learning orthographic transformations for object recognition”, in 1997 IEEE International Conference on Systems, Man, and Cybernetics, Orlando, FL, 1997.

G. Bebis, Georgiopoulos, M., and da Lobo, V. N., “Using self-organizing maps to learn geometric hash functions for model-based object recognition”, IEEE Transactions on Neural Networks, vol. 9, pp. 560-570, 1998.

G. Bebis, Georgiopoulos, M., Shah, M., and da Lobo, V. N., “Indexing Based on Algebraic Functions of Views”, Computer Vision and Image Understanding, vol. 72.3, pp. 360–378, 1998.

G. Bebis, Georgiopoulos, M., Shah, M., and da Lobo, V. N., “Using Algebraic Functions of Views for Indexing-Based Object Recognition”, International Conference on Computer Vision, pp. 634–639, 1998.

G. Bebis, Georgiopoulos, M., Shah, M., and da Lobo, V. N., “Algebraic functions of views for indexing-based object recognition”, in Proceedings of the Sixth International Conference, India, 1998.

G. Bebis, Georgiopoulos, M., and da Lobo, V. N., “Using Self-Organizing Maps to Learn Geometric Hash Functions for Model-Based Object Recognition”, IEEE Transactions on Neural Networks, vol. 9.3, pp. 560–570, 1998.

G. Bebis, Uthiram, S., and Georgiopoulos, M., “Genetic Search for Face Detection and Verification”, IEEE International Conference on Information,Intelligence and Systems, pp. 360–367, 1999.

G. Bebis, Deaconu, T., and Georgiopoulos, M., “Fingerprint identification using Delaunay triangulation”, IEEE International Conference on Information,Intelligence and Systems, pp. 452–459, 1999.

G. Bebis, Georgiopoulos, M., da Lobo, V. N., and Shah, M., “Learning affine transformations”, Pattern Recognition, vol. 32.10, pp. 1783–1799, 1999.

G. Bebis, Uthiram, S., and Georgiopoulos, M., “Face detection and verification using genetic search”, International Jornal on Artificial Intelligence Tools, vol. 9.2, pp. 225–245, 2000.

M. Bassiouni, Georgiopoulos, M., and Chiu, M., “Performance of standard and modified network protocols in a real-time application”, in 1997 International Performance, Computing and Communications Conference, Scottsdale, Arizona, 1997.

M. Bassiouni, Georgiopoulos, M., and Thompson, J., “Analytical and simulation models for real time networks”, in Proceedings of the 21st Annual Pittsburgh Conference, University of Pittsburgh, School of Engineering, Pittsburgh, Pasadena, 1990.

M. Bassiouni, Georgiopoulos, M., and Thompson, J., “Real time simulation networking Network modeling and protocol alternatives”, in 11th Interservice / Industry Training Systems Conference, Fort Worth, Texas, 1989.

H. Bahr, Georgiopoulos, M., and DeMara, R., “Integer-encoded massively parallel processing of fast learning Fuzzy ARTMAP neural networks”, in Proceedings SPIE; Conference of Applications and Science of Artificial Neural Networks III, Orlando, FL, 1997.